activity
20202024
most citedMulti-Correlation Siamese Transformer Network with Dense Connection for 3D Single Object Tracking

10 citations · 25 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.CV2024

Enhancing 3D Object Detection with 2D Detection-Guided Query Anchors

Haoxuanye Ji, Pengpeng Liang, Erkang Cheng

Multi-camera-based 3D object detection has made notable progress in the past several years. However, we observe that there are cases (e.g. faraway regions) in which popular 2D obje…

cs.CV2024★ 3 cited

CurveFormer++: 3D Lane Detection by Curve Propagation with Temporal Curve Queries and Attention

Yifeng Bai, Zhirong Chen, Pengpeng Liang +2

In autonomous driving, accurate 3D lane detection using monocular cameras is important for downstream tasks. Recent CNN and Transformer approaches usually apply a two-stage model d…

cs.CV2023★ 10 cited

Multi-Correlation Siamese Transformer Network with Dense Connection for 3D Single Object Tracking

Shihao Feng, Pengpeng Liang, Jin Gao +1

Point cloud-based 3D object tracking is an important task in autonomous driving. Though great advances regarding Siamese-based 3D tracking have been made recently, it remains chall…

cs.CV2023

CircleFormer: Circular Nuclei Detection in Whole Slide Images with Circle Queries and Attention

Hengxu Zhang, Pengpeng Liang, Zhiyong Sun +2

Both CNN-based and Transformer-based object detection with bounding box representation have been extensively studied in computer vision and medical image analysis, but circular obj…

cs.CV2022★ 1 cited

CurveFormer: 3D Lane Detection by Curve Propagation with Curve Queries and Attention

Yifeng Bai, Zhirong Chen, Zhangjie Fu +3

3D lane detection is an integral part of autonomous driving systems. Previous CNN and Transformer-based methods usually first generate a bird's-eye-view (BEV) feature map from the…

cs.CV2022

Traffic Context Aware Data Augmentation for Rare Object Detection in Autonomous Driving

Naifan Li, Fan Song, Ying Zhang +2

Detection of rare objects (e.g., traffic cones, traffic barrels and traffic warning triangles) is an important perception task to improve the safety of autonomous driving. Training…

cs.CV2022★ 3 cited

BEVSegFormer: Bird's Eye View Semantic Segmentation From Arbitrary Camera Rigs

Lang Peng, Zhirong Chen, Zhangjie Fu +2

Semantic segmentation in bird's eye view (BEV) is an important task for autonomous driving. Though this task has attracted a large amount of research efforts, it is still challengi…